Large organizations usually spread their research and development (R&D) around the world, hindering coordination efforts when performing future‐oriented technology analysis (FTA) studies. FTA is commonly used in R&D planning, especially on research prioritization. Therefore, we developed an FTA framework for large and geographically spread organizations, named Tiamat. The Tiamat framework is composed of a simplified organization model, which focuses on internal and external interactions during FTA, and an FTA process, which indicates the steps performed by the decision‐maker need until the delivery of the FTA final report from the organization. Based on the Tiamat framework, we developed the Tiamat software, a modular tool that implements generic FTA using the concept of workflows of FTA methods. Thus, we describe the architecture and collaboration aspects of the Tiamat software. The Tiamat framework (i.e., model and process) and the Tiamat software were applied in real situations to evaluate its FTA support capability. Besides, we show non‐FTA uses of the Tiamat software to showcase its flexibility. Among the contributions, we highlight the use of the Tiamat framework in the management of a standardized FTA process, based on the concept of workflows. The framework was developed to be easily adapted to many types of organizations, such as businesses, universities, and public institutions, either civil or military. The Tiamat software has shown to be capable to support distributed and local FTA studies, as well non‐FTA studies.

Os supercapacitores são dispositivos que acumulam energia elétrica e apresentam ciclo de vida longo, alta potência de densidade e baixo peso. Apesar dessas propriedades, eles possuem baixa capacitância e densidade de energia em comparação com outros dispositivos. Para avançar na aplicabilidade dos supercapacitores, é necessário desenvolver materiais de eletrodos que armazenem uma quantidade maior de energia. Com o objetivo de analisar as propriedades eletroquímicas de novos materiais aplicados em supercapacitores. Supercapacitores baseados em óxido de grafeno (GO) e óxido de grafeno reduzido (RGO) foram desenvolvidos neste trabalho. As morfologias de GO e RGO foram analisadas por microscopia eletrônica de varredura (MEV) e testes de cronoamperometria (AC) e voltametria cíclica (VC) para avaliar o desempenho eletroquímico dos supercapacitores. Os resultados do teste de MEV exibiram que o GO usado no experimento tinha uma estrutura porosa e baixa cristalinidade. De acordo com os resultados do teste ambos os supercapacitores têm características de capacitância semelhantes.

This article discusses the Brazilian maritime authority’s efforts to monitor and control vessels in specific maritime areas using data from the naval traffic control system. Anomalies in vessel locations can signal security threats or illegal activities, such as drug trafficking and illegal fishing. A reliable Maritime Domain Awareness (MDA) is necessary to reduce such occurrences. This study proposes a data-driven framework, CV-MDA, which uses computer vision to enhance MDA. The approach integrates vessel records and camera images to create an annotated dataset for a Convolutional Neural Network (CNN) model. This solution supports detecting, classifying, and identifying small vessels without trackers or that have deliberately shut down their tracking systems in order to engage in illegal activities. Improving MDA could enhance maritime security, including identifying warships invading territorial waters and preventing illegal activities.